Revolutionizing Cancer Detection with Optical Fibers and AI

Developing novel optical fibers and AI systems will revolutionize cancer detection and treatment by providing clinicians with valuable insights into cancerous tissue pathophysiological characteristics, enabling early and accurate detection, and improving patient outcomes.

Optical fiber technology has advanced significantly in recent years, leading to progress in diverse areas, such as high-speed telecommunications and high-power lasers. Within medicine, fibers have mainly been used as light-guides in endoscopes, but their potential for novel biomedical applications is vast. Developing novel fibers to evaluate and classify cancer tissue can aid in treatment decisions and improve patient outcomes.
AI systems and precisely-engineered optical fibers can revolutionize medical tools and diagnostics, including hyperspectral endomicroscopy and spectroscopy. Hyperspectral endomicroscopy can allow clinicians to capture high-resolution images of internal tissues and organs in multiple wavelengths, providing valuable insights into cancerous tissue. With AI-powered analysis, these images can be analyzed more accurately and efficiently, leading to better diagnoses and treatment plans. Spectroscopy, on the other hand, allows clinicians to obtain detailed information about the molecular composition of tissue. This can aid in the detection of early-stage cancer, as well as monitoring the treatment efficacy. By utilizing AI systems and advanced optical fibers, clinicians can combine the benefits of both endomicroscopy and spectroscopy to obtain a more comprehensive pathophysiological understanding of the underlying tissue. This could lead to earlier and more accurate diagnoses, as well as improved treatment outcomes.
The development of advanced optical fiber technology offers promising opportunities for commercialization, leading to more affordable and accurate cancer diagnostic tools. Utilizing for the first-time AI algorithms in conjunction with bespoke fiber systems can improve our ability to detect, classify, and treat cancer more effectively. By combining expertise from various disciplines, we can accelerate the translation of research findings into clinical applications, improving patient outcomes and enhancing the overall quality of healthcare.

Group Leader

Stephanos Yerolatsitis, Lindau Alumnus 2016
CREOL, University of Central Florida, USA

Skills for Project